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A Big Data Startup Factory: Frost Data Capital's Novel Recipe

Frost Data Capital is pursuing a model for building and selling companies focused on big data and analytics that breaks many of the assumptions of traditional VC funds and incubators. Frost Data Capital’s founders are betting their model will lead to predictable success that will attract a new class of older, more stable entrepreneurial leadership who will build companies that are precisely targeted to enterprise needs. The hoped for result is a more predictable series of significant but modest exits.

In essence the model amounts to this: By focusing on big data and analytics, assuming responsibility for coming up with the ideas, working with a network of large enterprises, employing seasoned, older executives as leaders, giving those leaders a stake in each others’ success, and providing lots of hands-on help, Frost Data Capital claims it will be able to make a much larger return for everyone involved.

The key element here is win-percentage. If Frost Data Capital’s forgoes larger wins but does not achieve a higher rate of success, it is hard to see how the lower returns will make up for the losses. But, if Frost Data Capital can make this work, and it seems that other investment firms have to some extent, then it may have created a new type of incubator. Let’s take a closer look at how Frost Data Capital seeks to make this model work.

Yeast cultures in an incubator (Photo credit: Wikipedia)

ThingWorx as a Case In Point

The purchase of ThingWorx by PTC last year provides an illustration of some of the principles that drive Frost Data Capital’s model. ThingWorx, an application building platform for the Internet of Things, was founded in 2009 by Russ Fadel, Rick Bulotta, and John Richardson. Fadel and Bulotta had previously founded Lighthammer, a system for manufacturing analytics that was purchased by SAP.

When they founded ThingWorx, Fadel and Bulotta had many of the elements of what Frost says matters in place. They were experienced leaders, they had many relationships with established enterprise companies, and they were focused on a big data problem, although, unlike Frost, application development rather than analytics was the focus.

ThingWorx executed with extreme focus, built the minimum viable product, got more wins, raised two rounds from Safeguard Scientifics, and then in 2013 they faced the challenge of scale, which led to a Frost-style exist. To fund the creation of a global sales team, ThingWorx either had to raise a significant amount of money, which would dilute the owners, or find another way of building a channel to reach a large number of customers.

Discussions of a partnership with PTC, a software company that creates products for product and service Lifecycle Management, led to an acquisition for $112 million, with an earn out potentially worth another $18 million. In the first quarter, backed by PTC’s guarantee of long term viability and its much larger sales force, ThingWorx sold more product than it had since it was founded.

This, as far as I can understand it, is sort of win that Frost is looking for. ThingWorx had a solid business and technology logic from day one. ThingWorx then created and expanded a minimum viable product. They make sure the product was relevant by using their established network of enterprise customers to validate their vision. The exit came without having to invest in a massive infrastructure for expansion.

While the exit price, $112 million, does not make the deal the next Google, it does provide a solid return for everyone involved. In addition, the ThingWorx executives now get to complete the product, grow the business, and reap further rewards with a lower risk profile.

How Could the Frost Model Work?

For Frost Data Capital to succeed it needs to change the win rate. Instead of getting a successful exit on 1 in 10 of its investments like a traditional Venture Capital firm, Frost aims to have half or more work out into an exit of from $100 million to $500 million. Let’s see how each of Frost’s assumptions contributes to this result.

Focus on Big Data and Analytics: Big data turns the lights on and allows the creation of high resolution models of business activity. In most cases, these models first allow re-engineering of processes for efficiency and increased automation and eventually lead to stronger predictions. This area is broad enough to encompass hundreds of companies in different industries, and narrow enough to allow patterns to be discovered.

Coming Up With The Idea: The Frost model is that its braintrust explores many ideas in conjunction with its enterprise partners and technology executives in its networks. While Frost may at times entertain pitches from entrepreneurs, the core model is that the braintrust selects and vets an idea and then assembles a management team. This model is a departure from most VC firms who field pitches, although it is not uncommon for a VC to assemble a team to pursue an idea that a partner feels strongly about.

Hyper Hands On Stewardship: While most VCs provide some vague promise of help, they rarely follow up besides attending board meetings and the occasional opportunistic meeting. The Frost model is that the VC braintrust engages fully and never leaves. Making this model work requires physical co-location of the management team in San Juan Capistrano in California, which could be a limiting factor for recruiting talent, although it doesn’t seem to have been an issue to date. Heavy involvement also limits the maximum number of companies that can be developed simultaneously. It will be interesting to see of the Frost team wearies of this model.

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An interesting aspect about the Frost Data Capital Shared Ownership Model is that the cap tables of startup companies is familiar to any VC with a common stock, an option pool and funds, and investors own preferred stock; however, the common stock is not broken down in the typical way.

There are three fundamental ownership pools:

1) Founding stock for the incubator executive team 2) A competitive stock package for the CEO & CTO 3) A shared pool for the CEOs and CTOs of the other portfolio companies

The shared pool element is key. If one of the startup companies succeeds, all of the senior staff of the other companies gets a small, but meaningful piece of the action. This creates a very powerful culture, where opportunities and challenges are freely shared across the Big Data and Analytics spectrum.

In addition to GE, Frost Data Capital has similar partnerships with other companies, including Intel, EMC and Accenture and it has started 17 companies so far with GE investing in a few of them. More on it at https://www.linkedin.com/today/post/article/20140717153721-4114386-ge-frost-i3-venture-capital-funding-and-incubator-for-the-industrial-internet-iot-and-big-data?trk=mp-reader-card